Exploiting characteristics of the Human Visual System (HVS) for the compression of video and still images is a field of active interest in video compression research. Several factors of varying significance have been discovered to influence human visual attention, such as motion, contrast, image element size, etc., and various techniques have been developed that attempt to define those regions in an image that are of greatest significance, such as those to which human visual attention is most sensitive. This significance information is then used to affect the compression of video/still images in a way that enhances the viewing quality of more significant regions. While this may be accomplished by using lower DCT quantizer values for more perceptually significant blocks, not all encoding standards support flexible alternation of the quantizer at the block or macroblock level.
HVS-significant image regions are particularly sensitive to distortions introduced by damaged or lost data and error propagation. In MPEG encoding, I-frames (INTRA-frames), in which complete image frames are encoded, are followed by one or more P-frames (INTER-frames) in which the difference between the current image frame and a previous image frame is encoded. To prevent error propagation among the P-frames until the next I-frame is reached, portions of the P-frames known as INTRA blocks are encoded as-is, without respect to previous frames. While various techniques for the spatial positioning of INTRA blocks within P-frames for error-resilient video encoding have been suggested, these techniques do not adequately take in account the mechanisms of the Human Visual System.
A technique for determining image block significance in terms of the Human Visual System that may then be adapted for optimizing standard encoding techniques with little or no increase in encoding/decoding overhead would therefore be advantageous.